In today's technologically-driven society, various computing systems implemented via computer software are increasingly serving as a backbone for providing various products and services to users. In order to reliably deliver, test, train, navigate, analyze, and extend these computing systems, it is increasingly important to develop a model understanding of both the expected and actual operation of these systems, which can be both verified and/or validated. While attempts have been made to build models of computing system behavior from user stories and documentation, such attempts have failed to overcome issues relating to missing data and requirement inconsistencies that are inherent in continuously developed user stories and documentation. For example, given a complete and detailed model of a desired computing system, there are testing systems that exist, which are capable of generating and executing tests to verify if the desired computing system satisfies some of the desired functionality as represented by the model. However, such existing systems cannot be utilized within continuous development environments, and their application within more static and slowly-changing development environments requires careful and time-consuming development of the desired computing system model. Additionally, such systems do not substantially eliminate the additional manual labor involved in generating the desired computing system model. Instead, existing testing systems often shift the manual effort from that of model development to one of detailed requirements development. Furthermore, existing testing systems cannot effectively relate generated models to user stories, requirements, or other data sources that may define the desired functionality of the computing system being tested. As a result, testing of the generated models generates tautological results of limited utility, and existing systems cannot discover discrepancies between a generated model and the desired functionality of the computing system being tested. Moreover, existing testing systems are incapable of producing tests that verify whether the desired functionality truly exists within the tested computing system.
As a result, it has become increasingly important that such computing systems operate as they are intended so as to ensure optimal service and minimal downtime for users. Given the complexity and criticality of many software computing systems, the testing of such systems is an important and often expensive aspect of product and computing system development. To that end, various systems and methods exist for evaluating computer systems, computer programs, and computing devices. For example, for traditional testing systems, it is necessary to start the testing process with manually developed models or very detailed system requirements. Unfortunately, such existing testing systems are not effective when dealing with continuously developed user stories and documentation that describe one or more features of a computing system being evaluated by the testing systems. Such ineffectiveness is often due to the time-consuming nature of complex model creation and maintenance.
Based on the foregoing, current testing technologies and processes may be modified and improved so as to provide enhanced functionality and features. Such enhancements and improvements may effectively decrease the manpower and effort required to generate models, tests, and test results, while simultaneously improving their coverage and accuracy. Additionally, such enhancements and improvements may provide for optimized model generation, higher quality validation testing, increased autonomy, improved interactions with users or devices, improved user satisfaction, increased efficiencies, increased access to meaningful data, substantially-improved decision-making abilities, and increased ease-of-use. Furthermore, such enhancements and improvements, particularly considering today's continual development environment, may assist in maintaining pace with development efforts.